Delivery of content in networking and system administration curricula involves significant hands-on laboratory experience supplementing traditional classroom instruction at the Ro...
Deep-layer machine learning architectures continue to emerge as a promising biologically-inspired framework for achieving scalable perception in artificial agents. State inference ...
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....
: This paper describes a research project that was carried out to determine and evaluate the learning environment customisations required to support selfmotivated, able, and experi...